Longitudinal monitoring of tumour burden with a modified Guthrie card

The ability to sequence DNA from a Guthrie card e.g. genomic or methylomic analysis (also see my post from last Summer) makes their more routine use in cancer genomics studies attractive. An area that would be great to see developed is the extraction of the cell-free DNA from a blood spot. This would be incredibly easy for patients to use and potentially allow very long term studies to be performed without visits to a clinic for a blood draw.

There are some big hurdles to overcome. A blood spot does not contain a lot of blood so the amount of cell-free DNA is likely to be very low restricting analysis to variants at high allele frequency. Also cell free DNA is likely to be contaminated with high-molecular weight genomic DNA, further diluting cell-free alleles. But for some applications this is not a problem.

Ideally cell-free DNA would be eluted/analysed separately from the genomic DNA from PBMCs for downstream mutation analysis. Current extraction methods lyse cells to extract maximum yield, but this lysis could possibly be avoided for ctDNA methods? The company Circulogene, spun out of Johns Hopkins in, is developing nucleic acid extraction products based on its proprietary Nanobind technology. Most recently their new pan-cancer NGS panel test was covered on GenomeWeb where Chen-Hsiung Yeh (CSO) described the 3,000 hotspot, 50 gene panel, which uses their ctDNA isolation technology. Technological improvements that allowed the use of dried blood spots may not be "on the cards" (sorry for the pun) for Circulogene, but I do hope someone is working on similar ideas.

Blood spot cards could be easily mailed out to patients and posted back to a central lab for processing. Adding information via 2D barcodes would allow fully automated test analysis so patients could be matched up to specific NGS panel tests.

AGBT16 it's the final countdown!

Saturday, February 13, 2016 14:45
Def Leppard are playing "Pour some sugar on me" while we wait for Nick Loman to walk on stage - not sure if this was intentional.

AGBT16 day 4: KAPA HyperDrive

Saturday, February 13, 2016 12:12:

Ross Wadsworth, KAPA Biosystems “Hyper Drive: high performance, streamlined workflows for RNA-seq and target enrichment”. KAPA Hyper (Covaris frag, fast efficient library prep), KAPA Hyper+ (enzymatic frag, fast efficient library prep), now RNA is getting the Kapa touch!

AGBT16 day 4: a new sequencing chemistry from Nanostring

Saturday, February 13, 2016 11:47:

Joe Beecham Nanostring “New optical barcode chemistry's power 3D biology & sequencing-simultaneous DNA, RNA, & protein analysis and low error-rate targeted sequencing” A sequencing system with no library prep or amplification - this is a pretty cool project. Joe is presenting something quite early on but wants to engage with the community on building out this chemistry.

AGBT16 day 4: Directed Genomics

Saturday, February 13, 2016 11:26:

Cynthia Hendrickson, Directed Genomics New England BioLabs “A novel fully customizable hybridization-based enrichment technology integrating capture and library preparation.” Cynthia was describing the new target capture chemistry she's been building with NEB. I wrote up an overview of their method in a post from last years AGBT. The method works with 10ng to 1ug of DNA from FFPE and FFZN (20-100ng inputs shown), and generates high-quality and fully automateable capture libraries in a 6-7 hour turnaround  with; 90% of reads on target, very high coverage uniformity and minimal GC bias. You can capture a single gene or many targets, allowing a single workflow  instead of having to choose between PCR or hyb-cap. The technology includes barcodes for up to 120 sample IDs at i7, and a 12bp UMI on the i5 end.

AGBT16 day 3 concurrent sessions: Nelson (C.elegans), Otto (FM ctDNA), Mungall (rearrangements)

Friday, February 12, 2016 21:10: I'm flitting between sessions tonight...first up is a talk by a users of my lab, we generated the data for several hundred C.eleganss genomes using Nextera and HiSeq 2500 - not quite a 1000 genome project yet!

Geoffrey Nelson 

Geoffrey Nelson, MRC Laboratory of Molecular Biology “A high-throughput genomics approach to efficiently link genes to phenotype”. The De Bono lab uses C.elegans as a model for how nervous systems coordinate behaviour, it's a good model as it has 20,000 genes but in a genome ust 100Mb in size.

AGBT16 10X early-access customer presentations

Stacey Gabriel

Stacey is the Director of the Genomics Platform at the Broad Institute. Gave us a brief look back to 2006: 117 instruments (GA's) producing 600,000 bases per day and 1 genome, versus 30 machines producing 12,000,000,000,000 bases per day and 32693 genomes!

AGBT16 10X Genomics workshop

10X Genomics were one of the stars of the show at AGBT15, this year they're bowling attendees over with new developments. They've obviously had an awfully busy year. They announced lots at JP Morgan (GenomeWeb, Core-Genomics). I got a sneak peak (as did Keith at OmicsOmics) to their announcements just prior to AGBT and am happy to share it with you now.

10X AGBT workshop: At today's AGBT workshop 10X filled in the gaps (excuse the pun) on what they've been doing and showed their new Chromium instrument ($125,000). This is an updated version of the original GemCode platform that runs new application specific reagent kits. They also showed data from the new application platforms: Chromium Genome, Chromium Exome, Chromium Single Cell.

Sequencing at AGBT

Contrary to what you might think this post is not going to be about the sequencing technology or data being presented at AGBT this year, but what could have happened several years ago and has come to AGBT16 - real-time sequencing.

AGBT16 day 3 plenary: Bielas, Piazzan and Kohn

Jason Bielas

Jason Bielas, Fred Hutchinson Cancer Research Center “Deep profiling of complex cell populations using scalable single cell gene expression analysis”. Early adopter of 10X single-cell RNa-seq platform - find out more at the 10X workshop this afternoon. Initially running experiments on PBMCs and finding multiple clusters, the number of these is very dependant on the number of cells profiled. Changing from 4500 to 16K cells increases resolution and they went up to 68K cells. They used a mixed 293T and Jurkat population to validate the single cell separation and found only ~1% doublets. They are now looking to use this system to recover single cell transcriptomes from mixtures, enumerate and classify different immune cells, and identify novel cell types; future work will loot to count tumour infiltration, investigate cSNPs, etc, ther are lots of potential apps.